Как лучше всего фильтровать группы по двум лямбда-условиям и создавать новый столбец на основе этих условий? ⇐ Python

[Anonymous]

This is my DataFrame:

import pandas as pd df = pd.DataFrame( { 'a': ['x', 'x', 'x', 'x', 'y', 'y', 'y', 'y', 'z', 'z', 'z', 'p', 'p', 'p', 'p'], 'b': [1, -1, 1, 1, -1, 1, 1, -1, -1, -1, -1, 1, 1, 1, 1] } ) And this the expected output. I want to create column c:

a b c 0 x 1 first 1 x -1 first 2 x 1 first 3 x 1 first 4 y -1 second 5 y 1 second 6 y 1 second 7 y -1 second 11 p 1 first 12 p 1 first 13 p 1 first 14 p 1 first Groups are defined by column a. I want to filter df and choose groups that either their first b is 1 OR their second b is 1.

I did this by this code:

df1 = df.groupby('a').filter(lambda x: (x.b.iloc[0] == 1) | (x.b.iloc[1] == 1)) And for creating column c for df1, again groups should be defined by a and then if for each group first b is 1 then c is first and if the second b is 1 then c is second.

Note that for group p, both first and second b is 1, for these groups I want c to be first.

Maybe the way that I approach the issue is totally wrong.


Источник: https://stackoverflow.com/questions/781 ... eate-a-new